WG 3: Algorithms and procedures

Leader: Prof. Alain Trémeau (FR), vice-leader: Dr. Orla Murphy (IE)

1st WG task st3.1.Registration processes (acquisition,filtering and view integration) Optical systems provide data for one field of view.As objects in general have to be monitored using many views, techniques are needed to merge individual views. Traditional techniques have physical impact on the surface, which is unacceptable for most CH objects. It is therefore necessary to identify, evaluate and classify available techniques for fusion of views.

2nd WG task st3.2 Integration of multi-sensor data Optical techniques for CH applications are contactless and carry certain information content, based on the interaction between light and surface. This interaction depends on the wavelength and the sensor used. Thus, information content can be extended by use of different instruments with varying spectral characteristics. A number of integrating steps are required, which have to be categorised and classified.

3rd WG task st3.3 data access and formats Measured data provide valuable content which shouldbe stored and made available to anyone using it for CH applications. However, due to characteristics introduced by the vendors of instruments or software there exist huge barriers to easy access. This situation has to be addressed and remedied, especially in interdisciplinary and multi-sensoral working fields.

2015

WG3 activities performed in 2015

Organisation of the COSCH Training School on "Heterogeneous visual data fusion techniques – acquisition and algorithms" in Szeged, Hungary, 7-9 December 2015.

The main objective of this Training School is to give an overview of current techniques (algorithms and complete processing chains) for transforming heterogeneous visual information into a common coordinate system in order to fuse acquired 3D and 2D data of CH objects into a coherent format which can be visualised or further analysed. Most of the topics which will be addressed are accompanied by appropriate open source code examples and explained on real life use cases.

This Training School seeks to establish a common understanding between engineers and CH experts working together on spectral and spatial data of CH objects. The basics of spectral and spatial data processing and fusion will be conveyed.

3D reconstruction of buildings based on fusion of heterogeneous data.

Meetings:

Cluj-Napoca, Romania, 18 September 2015 (5th Task force meeting)

Budapest, Hungary, 10 April 2015 (4th Task force meeting)

Saint-Etienne, France, 27 March 2015 (WG3 meeting)

Cork, Ireland, 13 February 2015 (3rd Task force meeting)

In connection with the COSCH MoU Objective PT4, WG3 addressed the following points:

a. Check if the structure of the COSCHKR knowledge schema is well adapted to describe the knowledge of all case studies supported by COSCH. The objective is to enrich this ontology from expert views.

b. Contribute to enrich the rules identified by adding new rules between classes and by improving the first rules identified. The idea was to exploit knowledge extracted from a literature review of papers related to different cultural heritage domains.

c. Contribute to enrich the rules listed in the COSCHKR knowledge schema by adding new rules related to the COSCHASM and by improving the first rules identified.

d. Document a higher number of algorithms (to enrich the COSCHASM), with a focus on some classes of algorithms (e.g. fusion of 2D colour/spectral images with 3D images – subtask 3.2) and document a higher number of common sequences of algorithms used in cultural heritage (from the case studies supported by COSCH).